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Forecasting of Sporadic Demand Patterns with Seasonality and Trend Components : An Empirical Comparison between Holt-Winters and (S)ARIMA Methods
Joint Authors
Sgarbossa, Fabio
Rimini, Bianca
Lolli, Francesco
Gamberini, Rita
Source
Mathematical Problems in Engineering
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-07-25
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Items with irregular and sporadic demand profiles are frequently tackled by companies, given the necessity of proposing wider and wider mix, along with characteristics of specific market fields (i.e., when spare parts are manufactured and sold).
Furthermore, a new company entering into the market is featured by irregular customers' orders.
Hence, consistent efforts are spent with the aim of correctly forecasting and managing irregular and sporadic products demand.
In this paper, the problem of correctly forecasting customers' orders is analyzed by empirically comparing existing forecasting techniques.
The case of items with irregular demand profiles, coupled with seasonality and trend components, is investigated.
Specifically, forecasting methods (i.e., Holt-Winters approach and (S)ARIMA) available for items with seasonality and trend components are empirically analyzed and tested in the case of data coming from the industrial field and characterized by intermittence.
Hence, in the conclusions section, well-performing approaches are addressed.
American Psychological Association (APA)
Gamberini, Rita& Lolli, Francesco& Rimini, Bianca& Sgarbossa, Fabio. 2010. Forecasting of Sporadic Demand Patterns with Seasonality and Trend Components : An Empirical Comparison between Holt-Winters and (S)ARIMA Methods. Mathematical Problems in Engineering،Vol. 2010, no. 2010, pp.1-14.
https://search.emarefa.net/detail/BIM-482272
Modern Language Association (MLA)
Gamberini, Rita…[et al.]. Forecasting of Sporadic Demand Patterns with Seasonality and Trend Components : An Empirical Comparison between Holt-Winters and (S)ARIMA Methods. Mathematical Problems in Engineering No. 2010 (2010), pp.1-14.
https://search.emarefa.net/detail/BIM-482272
American Medical Association (AMA)
Gamberini, Rita& Lolli, Francesco& Rimini, Bianca& Sgarbossa, Fabio. Forecasting of Sporadic Demand Patterns with Seasonality and Trend Components : An Empirical Comparison between Holt-Winters and (S)ARIMA Methods. Mathematical Problems in Engineering. 2010. Vol. 2010, no. 2010, pp.1-14.
https://search.emarefa.net/detail/BIM-482272
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-482272